PANDA: Processing-in-MRAM Accelerated De Bruijn Graph based DNA Assembly

TL;DR

PANDA is a novel Processing-in-MRAM platform that accelerates large-scale DNA assembly by leveraging in-memory logic operations, significantly reducing runtime and power consumption compared to traditional CPU and existing PIM platforms.

Contribution

This work introduces a hardware-friendly genome assembly algorithm and a data partitioning technique optimized for MRAM-based processing-in-memory architecture.

Findings

Reduces DNA assembly runtime by 18x compared to CPU

Cuts power consumption by 11x over CPU

Achieves 2-4x speed-up over existing PIM platforms

Abstract

Spurred by widening gap between data processing speed and data communication speed in Von-Neumann computing architectures, some bioinformatic applications have harnessed the computational power of Processing-in-Memory (PIM) platforms. However, the performance of PIMs unavoidably diminishes when dealing with such complex applications seeking bulk bit-wise comparison or addition operations. In this work, we present an efficient Processing-in-MRAM Accelerated De Bruijn Graph based DNA Assembly platform named PANDA based on an optimized and hardware-friendly genome assembly algorithm. PANDA is able to assemble large-scale DNA sequence data-set from all-pair overlaps. We first design PANDA platform that exploits MRAM as a computational memory and converts it to a potent processing unit for genome assembly. PANDA can execute not only efficient bulk bit-wise X(N)OR-based comparison/addition operations heavily required for the genome assembly task but a full-set of 2-/3-input logic operations inside MRAM chip. We then develop a highly parallel and step-by-step hardware-friendly DNA assembly algorithm for PANDA that only requires the developed in-memory logic operations. The platform is then configured with a novel data partitioning and mapping technique that provides local storage and processing to fully utilize the algorithm-level's parallelism. The cross-layer simulation results demonstrate that PANDA reduces the run time and power, respectively, by a factor of 18 and 11 compared with CPU. Besides, speed-ups of up-to 2-4x can be obtained over recent processing-in-MRAM platforms to perform the same task.